3.4-3.5
App Size Distribution
Heat maps visualize app size distribution for different categories.
Lifestyle apps: 288 apps between sizes 0-12, only 4 between 80-100.
Family and game apps: common with various sizes; numerous larger game apps.
App Price Trends
Majority of apps have lower prices.
Rarely, prices exceed $40-$50, such as one found in family apps.
Screen Time Analysis
Variation exists across apps concerning average screen time.
Gaming and education apps generally have higher screen time.
Entertainment apps (e.g., video apps) also see high usage.
Active Users & Installations
Distribution of active users varies, with some categories having higher numbers.
Installations reveal a mix of low and high numbers, consistently varying across types.
Advertisement Revenue Insights
Most apps generate low advertisement revenue, few achieve high revenue numbers.
Credo distribution (80/20 rule): 20% of apps generate 80% of revenue.
Key categories for revenue (games, family, social, news, lifestyle) exceed 70% of total revenue.
Revenue Decline Investigation
Week-over-week revenue has been decreasing since late January.
Investigation needed to understand the revenue drop.
Categories and Revenue Relationship
High screen time categories (games, family, social, news) correlate with high revenue.
Flat or slowly changing revenues or screen times observed in various categories.
Increased ad loads noticeable in the first weeks of the year, potentially leading to user decrease.
User Experience & Revenue Impact
User attrition occurs with increased ad display, impacting long-term revenue negatively.
Need to improve user experience by balancing ad exposure to maintain engagement.
Data Analysis with Python
Python code demonstrates data analysis techniques to extract insights.
Utilized libraries to analyze individual and multiple variables.
Building Interactive Dashboards
Dashboards are online reports enabling real-time data interactivity, such as Tableau.
Features include: displaying current revenue, active users, installs, and ad trends.
Users can select metrics of interest for targeted analysis.
Utilizing Dashboards for Decision Making
Dashboards provide immediate insight into revenue trends and potential issues.
They help identify correlations between ad frequency and user engagement.
Visualization enables easier understanding and faster decision-making regarding app performance.